The specific aims of the research proposed here are to 1) test predictions, made by computational models, regarding the relationship between theta rhythms and memory retrieval and memory strength; and 2) further refine and develop these models. These models and their predictions, if verified, carry direct relevance for the development of clinical therapies for disorders such as Alzheimer's disease, addiction, and post-traumatic stress disorder (PTSD). Under Specific Aim #1, I will provide rats with extensive experience in two environments. Defining features of these environments will include the enclosure lighting and the behavior-reward contingency. I will record the activity of place cells in the hippocampus and grid cells in the medial entorhinal cortex as the rats perform pure-environment trials and mixed-environment trials. During pure-environment trials, the environmental features will remain fixed throughout the trial; I will use these trials to characterize the spatial tunings of all of the cells (i.e., the spatial map) in the two separate environments. During mixed-environment trials, the environmental features will be flipped between those that define the separate environments multiple times during each trial. I will infer, based on the population activity, which spatial map is activated at each moment during these mixed-environment trials. In Experiment 1, I will test whether the moment at which one spatial map turns off and the other takes its place occurs non-uniformly over the phases of ongoing theta rhythms. In Experiment 2, I will test whether it is possible to induce the partial retrieval of a spatial map and thereby shift the point at which the alternate spatial map activates as was predicted by my previously proposed model. In Experiment 3, I will test the correspondence between the rat's behavior and which spatial map is activated to test whether such manipulations could serve as a clinical therapy to alter behavior. In Experiment 4, I will explore the relative timing of hippocampal and entorhinal remapping. Under Specific Aim #2, I will use computational modeling to support the empirical work described under Specific Aim #1. Specifically, I will use the same models that generated the predictions that I will address under Specific Aim #1 to simulate the task that I will use to test these predictions. From these simulations, I will generate synthetic data on which I will verify the data analysis methods that I will use to infer which spatial map is active at each moment. These simulations will also allow me to develop the stimulus control protocol, for use during Experiment 2 of Specific Aim #1, that will most reliably generate partial retrieval. Most powerfully, they will allow me to generate additional testable predictions regarding the boundary conditions of the predictions described under Specific Aim #1 and thereby motivate my next series of experiments.